Neural networks.
Given \(n\)  scalar inputs \(y_1,...,y_n\)  a perceptron performs the operation \(\sigma (\sum _i w_i \cdot y_i)\)  [1]}.
The parameters \(w_i\)  are called the weights or edges of the perceptron and \(\sigma (\cdot )\)  is the activation function.
The activation function \(\sigma (x)=\max (0,x)\)  is called ReLU. A perceptron can alternatively be called a neuron.
